ADME Evaluation in Drug Discovery

Medicilon's pharmacokinetics department offers the clients a broad spectrum of high quality of services in the areas of in vitro ADME, in vivo pharmacokinetics and bioanalysis services, ranging from small molecules to large molecules, such as protein and antibody. The animal species involved in our services are non-human primate, canine, mice, rat, rabbit and hamster. Meanwhile, non-human primate experimental platform and isotope platform for protein/antibody are certified by the Shanghai Government. Email:marketing@medicilon.com.cn Web:www.medicilon.com

For the development of bioactive molecules as therapeutic agents, oral bioavailability is often an important consideration.Therefore besides sufficient activity, an important goal for drug research is to gain sufficient understanding of the molecular properties that limit oral bioavailability to facilitate the design of new drug candidates. Now, the development of modern technologies, such as combinatorial chemistry and high throughput screening, into drug discovery has resulted in a vast increase in the number of lead compounds synthesized in pharmaceutical drug discovery setting. But in most cases such lead compounds demonstrate unfavorable biopharmaceutical properties, such as low oral bioavailability. It is believed that over 50% of the candidates failed due to ADME/Tox deficiencies during development.To avoid this failure at the development stage, a set of in vitro ADME screens has been implemented in many pharmaceutical companies with the aim of discarding compounds in early stage of drug discovery process. Even though the early stage in vitro ADME reduces the probability of the failure at the development stage, it is still time-consuming and resourceintensive.For this reason it is necessary to develop in silico methods for predicting drug-likeness.Many factors will influence oral bioavailability. Among them, human intestinal absorption may be one of the most important factors. Many in vitro cell culture models have been investigated as potential tools for drug absorption.The most widely used in vitro model is Caco-2 cell line.Caco-2 cells, a well-differentiated intestinal cell line derived from human colorectal carcinoma, display many of the morphological and functional properties of the in vivo intestinal epithelial cell barrier. Extensive studies have shown that human oral drug absorption and permeability coefficient have good correlations, suggesting that the human absorption can be well predicted by this in vitro model.5 Caco-2 culture models have many advantages. First, it measures the transport of the drug across a cell membrane, rather than an interaction of the drug with the lipid bilayer. Second, it can measure the parallel transport routes, both passive and active. However, it possesses several limitations including long preparation time, very slow absorption times compared to the human intestine, and large interlaboratory differences in quantitative results. In light of the limitations in throughput with these systems, the development of higher throughput computational tools for the reliable prediction of Caco-2 permeability is demanding. For a drug molecule across the intestinal epithelium, there are two important routes for permeation, including passive diffusion and carrier-mediated influx via active transport mechanisms.It is assumed that with only a few exceptions, these orally administered drugs were transported across the intestinal epithelium predominantly by a passive transcellular process. For passive diffusion, two types exist for permeation, the paracellular and the transcellular routes. Many factors will affect the passive intestinal permeability of a molecule including lipophilicity, hydrogen bonding capacity, solute size, and et al. Many physicochemical descriptors have been introduced to construct the Caco-2 permeability prediction models, including polar surface area hydrogen-bonding and size descriptors MolSurf-derived descriptors Volsurfderived descriptors MO-calculation membrane-interaction analysis and quadratic indices.Most of the earlier models using multiple linear regression (MLR) or partial least-squares (PLS) were based on a relatively small set of molecules and not fully validated by external prediction sets. For example, in Palm’s work, the training set only includes six molecules. Some QSPR models have relative good statistical significances, but their actual predictive abilities may be questionable. The reliable models can only be produced based on enough samples. In this study, we have investigated a number of different molecular descriptors and studied their relationships to Caco-2 permeation systematically. Our ultimate goal is to find a set of simple descriptors to estimate Caco-2 permeability as high throughput fashion. Moreover, to develop relatively universal predictive models, we used a large set of Caco-2 permeability data from a variety of sources. The whole data set includes 100 drugs or drug-like molecules. As far as we know, the data set used in this paper is much larger than those used in earlier works.